The system is designed, in part, to address a problem of a rapidly aging population in the United States that is placing a significant financial and logistical burden on the health care system, families, elderly individuals and older adults. According to a Congress of the United States Congressional Budget Office report entitled “Financing Long-term Care for the Elderly,” the cost of long-term healthcare services for older adults in the United States who suffer from physical and cognitive effects of aging was $135 billion U.S. in 2004. However, many of these older adults and individuals would prefer to remain in their homes, even as their health deteriorates, if they could be assured that someone would know when they suffered a health emergency so that they could receive medical care in a timely manner.
Currently, there are limited options for older adults suffering from health complications, illness, or the general effects of aging to live independently in their home without risk of experiencing a medical emergency that goes undiscovered for a potentially lengthy period of time. Many older adults that attempt to live independently suffer medical emergencies such as a fall, stroke, epileptic seizure, or diabetic coma. These medical emergencies are only discovered when a family member, friend, neighbor, caregiver or other individual calls and receives no answer, or physically visits the person and determines that the person has suffered a medical emergency. In many cases, a lengthy time between the start of the medical emergency and its discovery by a third party can result in trauma, severe and irreversible health damage, or even death. Furthermore, immediate discovery of a medical emergency is critical with many medical conditions, such as a stroke or heart attack, where minimizing the time between when the medical event occurs and the patient receives medical care can significantly impact the long-term health outcome as well as the associated costs of care.
To address these concerns, many older adults spend money out-of-pocket or use their health insurance to obtain in-home care. The caregiver may live in the home with the patient or may visit periodically to ensure the patient is okay. Because many older adults only need medical care if a medical emergency occurs, having a caregiver present to this degree is often beyond what the patient needs and impinges on their desire for privacy and independence.
Alternatively, many older adults move out of their homes into assisted living facilities where medical care is readily available should they need it. Frequently the older adult would prefer to remain in his or her own home, but due to concerns of burdening friends and family members with checking on them, or of suffering a medical emergency that goes undiscovered, chooses to move to an assisted living facility.
In either situation, there is a waste of resources by, and a loss of independence for, the older adult: either the patient is spending out-of-pocket or health insurance resources to pay a healthcare provider to be in the patient's home or the patient is spending these resources to stay in a typically expensive assisted living facility. In addition, the patient must compromise his or her desire for independence when a caregiver must live in or visit the home, or when the patient must leave his or her home and move into an assisted living facility, a family member's home, or some other living situation that provides some level of home monitoring.
Likewise, family members and friends may make sacrifices of time, money, and convenience to check in on the patient. They may need to take the time to periodically visit the older adult. They may also pay a caregiver to periodically visit the older adult or live in the patient's home, they may pay to house the older adult in an assisted living facility, or they may have the patient move into their home.
A final alternative is that the older adult chooses to remain in his or her home, with no third party individual checking in on or living with the person. In such cases, if a medical emergency occurs, it is likely that the emergency will not be discovered until significant health damage or death has occurred.
In addition, many facilities for the elderly, such as adult foster care homes and assisted living facilities, have multiple people that require monitoring. In such cases, the staff person or people responsible for the care of the older adults cannot monitor all of them 24 hours a day. Some facilities even offer a tiered or graduated structure for care in which the patient lives in his or her own home or apartment at the facility, only moving to living accommodations with more frequent monitoring when health issues warrant that higher level of monitoring and access to care. In these cases, medical care is available within the community, and the medical and facility staff may periodically check in on the patient. However, due to high patient-to-staff ratios, residents cannot be continuously monitored. This means that in some cases, they suffer a medical emergency with significant delay before someone discovers it. During this period of time, the older person's medical condition may worsen or permanent damage to the individual's health may occur.
Elderly adults that suffer from physical and cognitive effects of aging can live independently in their home much longer if a third party entity could monitor a patient remotely and receive an alert immediately if a medical emergency has occurred. Due to the high patient-to-staff ratios at assisted living facilities, the staff working in these facilities need assistance with monitoring older adults for medical emergencies.
The inventors have developed a set of devices, methods and a software system that can be used in an indoor environment, such as a home, apartment, hospital, or assisted living facility, to unobtrusively monitor a patient's movement patterns, detect changes over time, and thereby determine if the patient may have suffered a medical emergency and to alert one or more third parties that a medical emergency has likely occurred. The system also enables one or more third parties to unobtrusively conduct real-time monitoring of one or more patient's position and mobility within an indoor environment. The system uses this position and mobility information as a metric for assessing the person's health status over time and comparing current mobility metrics with long-term trends.
The devices, methods, and software system disclosed herein will be useful in unobtrusively monitoring multiple older adults living in a multi-patient facility, such as an adult foster care home, assisted living facility or retirement community with graduated levels of residence options based on the level of required monitoring and care. In such cases, the person responsible for the resident in the facility may need to monitor several residents who may be in separate rooms in the home. For these staff members, the ability to receive alerts immediately when a medical emergency occurs can enable the staff person to provide immediate medical care or ensure the elderly patient or resident receives immediate access to medical care from a medical provider.
The invention presented herein is a valuable component for enabling older adults to live independently longer. The invention is designed to be a state-of-the-art mobility and health assessment technology that keeps track of location and movement patterns of a person within their home and notifies the older person, friends, family, and/or health care professionals if there is a change in the person's health as assessed based on changes in these movement patterns and activities of daily living. The invention will enable an older adult to live independently within their home or in an assisted living facility without fear that an emergency event might happen without anyone being aware that such an emergency has occurred. The invention will provide peace of mind to these older persons' families and friends who worry about their well-being. The invention will also be of significant benefit to researchers who monitor mobility in older populations during clinical trials for assessing the effectiveness of drugs, surgical procedures, and other treatments for illness in older people.
The invention represents a major leap forward in health monitoring for the elderly due to several key innovations which make the invention the most accurate and reliable method for monitoring mobility and health of a person non-invasively within their home. The invention consists of three modes of operation for performing mobility estimation: 1) a tag-based mode of operation which requires the older adult being monitored to wear a tag on their wrist, ankle, or around their belt, or elsewhere on their body or clothing; 2) an unobtrusive, passive, tag-free position estimation mode of operation which requires no compliance by the older adult being monitored for the case where the older person forgets or chooses not to wear the tag; and 3) a combination of the two above modes of operation whereby mobility is estimated based on a tag-based mobility estimation mode of operation and a tag free mobility estimation mode of operation.
The tag-based mode of operation (see FIG. 4 for illustration of tag, access-points, and hub), designed using time-of-flight wireless radio transceivers, inertial sensors (3-axis accelerometers and gyroscopes), and Bayesian tracking algorithms, will provide accurate sub-meter location and walking speed, detailed movement patterns, derived activities of daily living (bathroom trips, meals, etc.), and information on gait and falls. The tag-free mode of operation does not require a tag to be worn and instead uses advanced classification algorithms that evaluate disruptions in radio frequency (RF) signals between wall-mounted access points as a person walks freely through their home. The tag-free mode can estimate locations within 2-3 meters of accuracy, assess whether multiple people are in a room (assessing social interaction), and potentially indicate falls; this technology avoids privacy issues with alternative video based surveillance, and far supersedes current tag-free position estimators such as those based on infrared motion sensors. As noted above, the invention may be based on using the tag-based mode, the tag-free mode, or a combination of the two.
The inventions described herein represent a major advance in elder care monitoring because they deliver superior tag-based and tag-free mobility assessment and tracking in an easy-to-use and easy-to-install system that is affordable. The inventions have the potential to become the standard of care for 1) enabling older adults to live independently within their own homes for a longer period of time, 2) improving assisted living care for older adults living within care facilities, and 3) delivering superior mobility metrics for research groups who are assessing affects of drugs, surgery, and other therapies on mobility in clinical trials.
Over the last decade, the inventors and their colleagues have installed and evaluated many tracking and in-home health monitoring systems, and have developed approaches for gathering such data unobtrusively. For the most part these methods have allowed at best room-level tracking and are insufficient for identifying key instrumental activities of daily living. While the global positioning system (GPS) has provided standardization for ubiquitous outdoor localization, such systems do not exist indoors. Tags based on RFID, IR, or ultrasound, developed by such companies as Inlocality, Radianse, Awarepoint, and Sonitor, are marketed directly to the healthcare profession for hospital applications, but provide only room level localization at best and are inadequate for extracting activities of daily living (ADL) or other aspects of mobility. A number of companies (e.g. Ekahau Inc, HomeFree Systems) have released tracking tags based on Receiver Signal Strength Indicator (RSSI) positioning using 802.11 standard Wi-Fi routers that purport to achieve localization accuracy of a few meters. In practice, these systems are difficult to calibrate, have poor sample rates and battery life, are plagued by interference issues, and in general exhibit poor performance as observed in our own studies.
A newer approach called ultra-wideband technology (UWB) uses spread-spectrum coding to implement time-difference-of-arrival (TDOA) from a small tag and multiple proprietary based stations. UWB allows for very accurate localization; however, existing commercial systems (e.g. Ubisense, Thales, and RoundTrip), are extremely costly, exceeding tens of thousands of dollars for installation of the base stations. The proprietary base stations are also large, require special wiring, and as such are just not appropriate for most in-home monitoring applications. The selection of technologies for unobtrusive tag-free tracking is even more limited. Due to privacy issues, video based tracking is not an option for most in-home monitoring applications. Simple binary Infra-red (IR) motion detectors may be used to determine region level location (e.g., X-10 IR motion sensors, Versa), but again do not provide accurate activity and mobility information and have issues when more than one individual are in the living space. Additional resolution is possible with arrays of sensors. Mitsubishi Electric Research Laboratories, for example, has a prototype system that requires over 200 IR sensors to be installed in the ceiling of a large office building.
The inventors have experimented with using small linear arrays of IR motion sensors to extract walking speed along a hallway. In general, such arrays are difficult and costly to install. Contact switches may also be placed in doors, beds, or toilets, to help provide localization. The inventors have evaluated many of these systems and all off-the-shelf positioning tracking devices have been found to be unreliable, inaccurate, not scalable, and unable to extract fine details of mobility necessary for meeting the inventors' needs. In one study, use of commercial tag based systems were abandoned because they 1) failed to accurately track 3-d position of the older persons within their homes and 2) because the ongoing maintenance, calibration, and service of these systems proved to be too costly and resource intensive to continue using them. Furthermore, no system currently exists that can provide both position tracking and extraction of other aspects of mobility and health status. The lack of an existing system meeting the needs identified by the inventors has been a primary driver in why the inventions disclosed herein have been designed to meet the needs of the aging population.
This invention addresses many of the shortcomings of existing tracking and monitoring solutions. The invention moves beyond simple passive monitoring of location with the ultimate ability to assess an older person's health based on changes to daily mobility patterns as they move throughout their living environment. Of course, it should be understood that the system may be used in other applications as well, beyond older individuals. For example, people with conditions that impair their movement, such as multiple sclerosis, may enhance their ability to live alone by using one or more of the systems disclosed herein.
As described below, multiple key innovations distinguish the inventions described herein from existing tracking methodologies and systems. Five such innovations are described below. It should be understood that the systems described herein may be based on one or more of these five innovations. Such systems can consist of any one or more of these innovations, consist essentially of any one or more of these innovations, or include any one or more of these innovations.
Innovation 1: Highest accuracy integrated navigation solution that combines Bayesian estimation algorithms with time-of-flight sensors and inertial measurement sensors (accelerometer and gyroscope) to achieve multi-scale tracking capabilities.
The invention achieves the most accurate tag-based tracking performance possible by combining time-of-flight (TOF) ranging sensors and inertial measurement sensors with the most technically advanced Bayesian tracking algorithms currently available. By integrating the inventors' Bayesian state estimation algorithms based on sigma point Kalman filtering (SPKF) with TOF ranging sensors, position tracking accuracy as high as 0.55 meters has been demonstrated which is critical for using mobility as an assessment of health status and changes in activities of daily living. This accuracy is 4 times better than off-the-shelf solutions which use the same hardware but inferior tracking algorithms. Although accuracy to 0.55 meters has been attained, accuracy to 0.6, 0.7, 0.8, 0.9, 1.0, 1.5, 2.0 meters also can be used if desired for various reasons, e.g., cost of system. Therefore the invention should be understood to include a wide range of position tracking accuracies.
The invention also incorporates an inertial measurement unit (IMU) including 3-axis accelerometers and gyroscopes into the design, which in combination with SPKF enables even further increase in tracking performance. The IMU in combination with TOF metrics enables accurate high-bandwidth 3D trajectory estimates with better than centimeter (relative) precision for monitoring precise movement patterns (e.g., gait features and falls). This two-scale performance capability (grosser level using TOF and more precise using TOF plus IMU) is unavailable in all commercial indoor tracking systems and will enable the invention to be used in a far broader array of mobility monitoring and health assessment applications.
Innovation 2: Truly non-obtrusive (i.e., no video monitoring) tag-free tracking for situations when an individual declines or forgets to wear their tag.
While the superior accuracy of this invention's tag-based position monitoring technology is a major innovation, seniors (especially those with cognitive decline) cannot always be relied upon to wear their tag. In addition, many healthy older adults would simply prefer not to have to wear any device. This is why the inventor's tag-free tracking solution is another primary innovation of this invention. The tag-free tracking method is based on the principle that radio frequency (RF) energy between two or more RF transceivers reflect and absorb differently depending on where a person is located within that room. The same wall-mounted access points and hub used in the tag-based tracking mode are used in tag-free mode; however, no tag is required; the older person is not required to wear anything for tracking purposes. The access points and hub are configured to transmit and receive signals (RSSI, link quality, and TOF) between each other. Any motion of a person through the room will change the RF reflection patterns of the radio waves within the room which can be measured by the access points. An algorithm or a classifier such as a neural network, Gaussian mixture model, or k-means classifier may then be used to determine a person's location to specific regions within the room with an accuracy of 2-3 meters. The tag-free mode of operation can also determine whether one or more people are present in a room, which is of critical importance for use in monitoring social interaction.
This innovation represents a significant improvement over the state-of-the-art (IR-based monitoring technologies, which have only room-level present/not-present accuracy) enabling unobtrusive monitoring of movement patterns, walking speed, and measures of overall activity. The tag-free system could be a replacement technology for IR-based monitoring, which typically delivers only binary room-level information localization, or where one needs to be able to identify when multiple people are present.
Innovation 3: Advanced approach to auto-calibration to achieve a simple “plug-and-play” installation.
No matter how beneficial or useful a tag-based or tag-free senior monitoring system may be, no one will ever use it if it is too difficult to install and use. Current tag-based systems that use RSSI as the location metric, for example, can take days of collecting data in every room to carefully calibrate, and then repeated calibration is often necessary every month. This adds significant cost to the maintenance of such systems. This is where the current invention provides a third innovation. The system uses a method called simultaneous localization and mapping (SLAM) for automatic calibration. SLAM will enable the access points to determine their geometric location and necessary calibration parameters within a home automatically by sending wireless messages to each other and assessing their relative position based on TOF measurements. Implementation of SLAM will minimize any calibration that will be required for the system to function properly such that a user of the system will be able to simply plug the access points into their wall sockets at home and begin monitoring.
Innovation 4: Designed to monitor activities of daily living, assess health changes over time, and provide emergency alerts.
The tracking and movement monitoring capability of the system described in this invention will also enable automated extraction of observations or activities of daily living (ADL). The system includes extraction of such metrics as number of trips to the bathroom or time spent in the kitchen, as well as other indicators of activity such as variance in walking speed, or time spent in bed, sitting, or walking. While a few companies (WellAware, GrandCare) offer monitoring of ADL based on IR motion and contact type switches, this invention describes a newer better solution combining both tracking and advance mobility assessment through either tag-based or tag-free modes.
The system will be capable of sending emergency alerts to family members, friends, or health care professionals in the event that something has changed significantly in the older person's health status. If the person has developed a change in activity pattern due to a fall or a stroke, the system will detect that and send an alert so that someone may be dispatched to help the older person. If the older person has slipped and fallen in the shower and they are lying in the bathroom, the system will automatically send an alert message to a family member of what has occurred.
Innovation 5: Information system (IS) to enable seniors to be monitored by friends, family and health providers.
The system described in this invention is designed to be scalable, allowing it to be used to track one person living alone in an apartment or as many as hundreds of people living within an assisted living environment. Each tag will have a unique ID associated with it that will allow the system to independently track multiple people either within a home or an assisted living care facility. One implementation of the system has been designed to work at the 2.4 GHz digital spread-spectrum (DSS) frequency using a custom self-correcting ad-hoc wireless network configuration. A server is described which includes a database and Internet application running on a server for storing movement patterns and for sending alerts to friends, family members, and health care providers in the event of an emergency. In addition to being used in the home health and assisted living settings, it will be useful for research groups using the system to study drugs, surgery and other therapy that impacts mobility and activity; de-identified data of movement patterns can be available to researchers in real time using a standard web browser or mobile computing device such as a phone. This information system (IS) provides a further opportunity for innovation as it leverages the ubiquitous availability of cell phones to enable the creation of a social network of older adults and friends, all living independently within their own homes who can then self-monitor each other using the system.
Patent Reviews: Many patient monitoring devices are designed to capture and record physiologic data and send it to a central software application. For example, US Patent Publication No. 20060235281 “Wireless patient monitoring system” by Mark Joseph Tuccillo (Assignee: Ivy Biomedical Systems, Inc.) uses sensors and a transceiver to capture and send physiologic data like that captured by an ECG monitor or oximeter to a central clinical system as the patient moves through a hospital. U.S. Pat. No. 6,870,484 “Patient monitoring systems having two-way communication” by James Brinsfield and Michael F. Steinike similarly transmits physiologic data to a central clinical system and receives data from the system. US Patent Publication No. 20040102683 “Method and apparatus for remotely monitoring the condition of a patient” by Sukhwant Singh Khanuja et al. remotely monitors physiologic data such as blood pressure, pulse rate, blood glucose, weight, pulse oximetry and others. The invention described herein differs from these patents because it extracts health status information using movement patterns rather than physiologic data.
Other patient monitoring systems monitor for the patient's physical location within an interior environment, but do not use TOF, RSSI and link quality data for continuous monitoring. For example, U.S. Pat. No. 7,666,151 “Devices and methods for passive patient monitoring” by Patrick K. Sullivan et al. uses piezoelectric sensors placed on a flat surface or pad that the patient may frequent such as a chair, wheelchair, or under a layer of bedding, to monitor the patient's location. Numerous inventions are designed to monitor the location of individuals within an interior environment who are not necessarily older or frail; for example, some of these devices detect when an intruder has entered a home or other building. Other inventions are designed to monitor the basic location of inventory items.
US Patent Publication No. 20090322513 “Medical emergency alert system and method” by Franklin Dun-Jen Hwang et al. tracks the location and physiologic data of multiple older adults in an assisted living facility, retirement community or other similar defined community using a wearable device by measuring receiver signal strength indicator (RSSI) or time of flight (TOF) data within a defined interior or exterior environment. The invention also tracks the position of each patient using GPS data, which is useful for capturing location data when the patient leaves the defined interior and exterior environment. The invention sends location and physiologic data to a remote monitoring station in a central monitoring center with trained individuals and some physicians. The wearable device relies on an impact sensor to determine if the person has fallen. It also uses a microphone that captures a high-frequency yell followed by moans from the patient to determine that the patient has fallen.
The current invention is different from the invention described in this patent publication primarily because the current invention uses position and mobility information as the metric for determining if an emergency has occurred—for example if the person's walking speed has changed, it could be an indication that a stroke has occurred. Or if the person is twice as active as they have been over the prior 6 months, perhaps they are suffering from a urinary track infection. Patent Publication no. 20090322513 uses the position information only to notify emergency personnel of the individual's location if an emergency is detected. The position and mobility information is not used to detect or monitor the health status of the individual. In Patent Publication no. 20090322513, the physiologic data that is transmitted by the system is what is used to determine the health status of the individual, not the mobility information. Furthermore, while time-of-flight is mentioned briefly in the description of the patent, the claims only mention RSSI as the metric for determining the position of the individual within the environment. Whereas, the current invention specifically claims use of time-of-flight information, RSSI, and link quality for determining the position of the individual when using tag-free tracking.
Some patient monitoring systems use optical signals to detect motion. U.S. Pat. No. 7,196,317 by Kenith Meissner et al. uses optical signals and the interruption of these signals that occur as a means of detecting motion.
U.S. Pat. No. 7,394,385 “Comprehensive monitoring system” by Thomas S. Franco, Jr. and William G. DiMario discloses an invention that determines if an individual has fallen using a patient-worn accelerometer or plurality of accelerometers. Franco and DiMario use sensors to collect some patient physiologic data and environmental data such as humidity and temperature, and use receiver signal strength indicator (RSSI) measurements to determine patient location. Franco and DiMario do not use time-of-flight information to determine the patient's location. Furthermore, their system does not include a tag-free method of determining the individual's location.
U.S. Pat. No. 6,466,125 “System and method using impulse radio technology to track and monitor people needing healthcare” by James L. Richards et al. uses wideband technology and pulses to enable a patient to notify medical personnel if an emergency has occurred and to help medical personnel determine an emergency victim's location once they arrive on the scene of the emergency. As with patent publication no. 20090322513, this patent does not use movement patterns to monitor health status, but only to identify where the person is located should they indicate themselves that an emergency has occurred by pressing a button. Furthermore, this invention does not describe a tag-free method of monitoring health status should the individual fail to wear their tracking tag, whereas the current invention does include this functionality.
U.S. Pat. No. 6,466,609 “Method for wireless information transfer” by Manfred Koslar et al describes the use of chirp spread-spectrum (CSS) to determine an individual's position, while U.S. Pat. No. 6,404,338 “Measuring and/or security system” by Manfred Koslar discloses using CSS to determine an individual's position for detecting the distance of an object or person and for determining when that object has been moved; for example, in the case of an object, if the object has been stolen. These patents are different from the current invention because they are not using the position information to assess health status or send emergency alerts in the case of a change in health status.
U.S. Pat. No. 6,753,782 “System for monitoring older adults with Alzheimer's disease or related dementia” by Michael W. Power uses RSSI to monitor the behavior, behavior patterns, and movements of older adults with Alzheimer's disease or related dementia as well as other conditions such as autism, attention deficit disorder (ADD), or schizophrenia by placing a detector at the location of a hazard or other location to be monitored and determining when the patient gets too close or far away from the location. Power's invention uses RSSI for tag-based patient localization, while the current invention uses time-of-flight as the metric for tag-base patient localization.